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. Strong knowledge of quantitative and/or computational research methods, ideally in econometric analysis or optimization and simulation models. Preferable knowledge in Python and STATA. A collaborative team
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for its strength in optimization, optimal control, dynamical systems, and applied mathematics in general. Mobile working A certified (Audit berufundfamilie) family-friendly work environment. Berlin is one
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Organisation Job description Project and job description Our project will make use sensing technologies (hyperspectral cameras, NIR and Raman sensors), and an edge-compute AI pipeline to sort used
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, Industrial Engineering, Computer Science, or Machine Learning. Solid experience with quantitative optimization methods, including (but not limited to) mathematical programming and stochastic dynamic
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candidate with a strong background in computational fluid dynamics (CFD) and specialized expertise in hemodynamics associated with coronary artery disease (CAD). The ideal candidate will hold a PhD in
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analysis. Experience in formulating and solving mathematical optimization problems is an asset. Proficiency in English is required; good comprehension and oral communication skills in German are desirable
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Engineering, and Engineering Management. Students with interests in computational mechanics, optimization design, bioinspired design, sustainability management, machine learning, AI, uncertainty quantification
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academic partners in Europe and globally. Candidates with the following qualifications will be preferred: Educational background in power systems. Documented knowledge in optimization in power and energy
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represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster networking, enable internationalization and
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optimization. An ideal candidate is expected to have a strong interest in theoretical and innovative research. To apply. Please contact the supervisor, Dr Chao Chen - chao.chen@manchester.ac.uk . Please include